Professional networking is the tool of today for the improvement of circumpolar health and wellbeing
Bibliographic record
Abstract
Professional collaboration is continuing in the field of Circumpolar Health. A special editorial of this issue describes the Circumpolar Health Symposium on “Populations in Transition: Health of Circumpolar Indigenous People” held in Toronto in February. A Tele-health conference will be held this month in Anchorage, the IASC-workshop for “Nutrition and Health” in May in Oulu, a Symposium for “Problems of Human Health and Physiology in the North” in June in Syktyvkar, Komi, Russia (erbojko@physiol.komisc.ru). During the coming autumn, there are many other meetings, many of which are now announced in this issue. The WHO European office arranged an expert meeting on “Public Health Responses to Extreme Weather and Climate Events” in February, pointing out the importance of the awareness of public health to heat waves and cold spells in countries from the South to the North. WHO will continue the preparation for the recommendations on this topic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.038 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".